Journal cover Journal topic
Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
https://doi.org/10.5194/hess-2017-598
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
Research article
03 Nov 2017
Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Hydrology and Earth System Sciences (HESS).
Intercomparison of different uncertainty sources in hydrological climate change projections for an alpine catchment (Clutha River, New Zealand)
Andreas M. Jobst1, Daniel G. Kingston1, Nicolas J. Cullen1, and Josef Schmid2 1Department of Geography, University of Otago, Dunedin, P.O. Box 56, New Zealand
2Department of Geography, University of Munich (LMU), Munich, Germany
Abstract. As climate change is projected to alter both temperature and precipitation, snow controlled mid-latitude catchments are expected to experience substantial shifts in their seasonal regime, which will have direct implications for water management. In order to provide authoritative projections of climate change impacts, the uncertainty inherent to all components of the modelling chain needs to be accounted for. This study assesses the uncertainty in potential impacts of climate change on the hydro-climate of New Zealand’s largest catchment (the Clutha River) using a fully distributed hydrological model (WaSiM) and unique ensemble encompassing different uncertainty sources: General Circulation Model (GCM), emission scenario, bias correction and snow model. The inclusion of snow models is particularly important, given that (1) they are a rarely considered aspect of uncertainty in hydrological modelling studies, and (2) snow has a considerable influence on seasonal patterns of river flow in alpine catchments such as the Clutha. Projected changes in river flow for the 2050s and 2090s encompass substantial increases in streamflow from May to October, and a decline between December and March. The dominant drivers are changes in the seasonal distribution of precipitation (for the 2090s +25 to +76 % in winter) and substantial decreases in the seasonal snow storage due to temperature increase. A quantitative comparison of uncertainty identified GCM structure as the dominant contributor in the seasonal streamflow signal (44–57 %) followed by emission scenario (16–49 %), bias correction (4–22 %) and snow model (3–10 %). While these findings suggest that the role of the snow model is comparatively small, its contribution to the overall uncertainty was still found to be noticeable for winter and summer.

Citation: Jobst, A. M., Kingston, D. G., Cullen, N. J., and Schmid, J.: Intercomparison of different uncertainty sources in hydrological climate change projections for an alpine catchment (Clutha River, New Zealand), Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2017-598, in review, 2017.
Andreas M. Jobst et al.
Andreas M. Jobst et al.
Andreas M. Jobst et al.

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